1. Field of the Invention
The present invention relates to a machine tool controlled by a numerical controller with a function to determine a replacement time for a maintenance component.
2. Description of the Related Art
The life of a machine tool is extended by appropriate maintenance work and component replacement. A controller that controls the machine tool manages times for maintenance work and component replacement for various components used in the machine tool. For example, the maximum number and duration of operations obtained by lifetime experiments during design of the machine tool are stored in advance in a storage device of the controller for the machine tool as reference values. The controller for the machine tool measures the current number and duration of operations of a component to be monitored. When the measured number and duration of operations reach the respective preset reference values, a user of the machine tool is informed that the time has come to maintain or replace the component to be monitored.
For the values of the maximum number and duration of operations for determining the life of the component used in the machine tool, margins are allowed for values obtained by lifetime experiments during design taking various usage environments for the machine tool into account. Setting the values of the maximum number and duration of operations in this manner has the advantage of allowing the life of the component to be easily managed. However, under service conditions for most machine tools, the user is requested by the controller for the machine tool to maintain or replace the component earlier than the end of the inherent life of the component. This leads to frequent maintenance work and component replacement, increasing costs.
On the other hand, when a component of the machine tool is used under a condition and an environment which fail to meet a certain specification, maintenance work or component replacement becomes necessary earlier than the expected end of life of the component, but the controller for the machine tool fails to request the user to maintain or replace the component earlier. This precludes the component from being appropriately maintained or replaced. Thus, disadvantageously, the maintenance or replacement of the component may be delayed to damage the machine tool including the component, shortening the life of the machine tool.
An abnormality diagnosis apparatus is disclosed in Japanese Patent Application Laid-open No. 5-101245. Replacement history information on a component forming an abnormality diagnosis target device is input to and stored in the abnormality diagnosis apparatus in association with the number of the device. Component replacement information is estimated based on the replacement history information and already input and stored abnormality diagnosis data. The estimated component replacement information is output to and displayed on a display device.
The abnormality diagnosis apparatus can contribute to taking corrective measures after the abnormality diagnosis target device becomes abnormal. However, the abnormality diagnosis apparatus fails to diagnose reduced responsiveness resulting from degradation of the component as abnormality. The abnormality diagnosis apparatus fails to indicate an accurate maintenance time before the abnormality diagnosis target device becomes abnormal.
Furthermore, a monitoring diagnosis apparatus that diagnoses for the cause of abnormality is disclosed in Japanese Patent Application Laid-open No. 2011-243118. The monitoring diagnosis apparatus divides detection section data collected from a plurality of detection sections of a monitoring diagnosis target device into a plurality of status mode-based detection section data based on status mode transition points detected by a status mode transition point detection processing section. Moreover, the resultant status mode-based detection section data are classified into a plurality of groups. For each status mode and for each group, each of the detection data is compared with past statistical data to allow abnormality of the device to be detected. Then, for states before and after the detection of the abnormality, models for links among the detection section data and among the groups are constructed based on correlation coefficients for the detection section data for the respective status modes and the respective groups. Then, the cause of the abnormality is diagnosed based on the link model for the state before the detection of the abnormality and the link model for the state after the detection of the abnormality.
The monitoring diagnosis apparatus can efficiently and accurately analyze the complicated cause of occurrence of abnormality. However, the monitoring diagnosis apparatus fails to target reduced responsiveness resulting from degradation of the component for monitoring diagnosis. The monitoring diagnosis apparatus thus fails to inform the user of an accurate time for maintenance work before the abnormality diagnosis target device becomes abnormal.